Bi-VLA: Vision-Language-Action Model-Based System for Bimanual Robotic Dexterous Manipulations

This research introduces the Bi-VLA (Vision-Language-Action) model, a novel system designed for bimanual robotic dexterous manipulation that seamlessly integrates vision for scene understanding, language comprehension for translating human instructions into executable code, and physical action generation. We evaluated the system's functionality through a series of household tasks, including the preparation of a desired salad upon human request. Bi-VLA demonstrates the ability to interpret complex human instructions, perceive and understand the visual context of ingredients, and execute precise bimanual actions to prepare the requested salad. We assessed the system's performance in terms of accuracy, efficiency, and adaptability to different salad recipes and human preferences through a series of experiments. Our results show a 100 % success rate in generating the correct executable code by the Language Module, a 96.06 % success rate in detecting specific ingredients by the Vision Module, and an overall success rate of 83.4 % in correctly executing user-requested tasks.

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Publication Details

Published
2024-10-06
DOI
https://doi.org/10.1109/smc54092.2024.10831380
Citations
16
Primary Topic
Robot Manipulation and Learning
Type
article
Field-Weighted Citation Impact
5.25
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article

Bi-VLA: Vision-Language-Action Model-Based System for Bimanual Robotic Dexterous Manipulations

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article

Bi-VLA: Vision-Language-Action Model-Based System for Bimanual Robotic Dexterous Manipulations

Miguel Altamirano Cabrera, Dzmitry Tsetserukou, Artem Lykov, Ali Alabbas, Koffivi Fidèle Gbagbe, Oussama Alyunes
article en
16 citations

Abstract

This research introduces the Bi-VLA (Vision-Language-Action) model, a novel system designed for bimanual robotic dexterous manipulation that seamlessly integrates vision for scene understanding, language comprehension for translating human instructions into executable code, and physical action generation. We evaluated the system's functionality through a series of household tasks, including the preparation of a desired salad upon human request. Bi-VLA demonstrates the ability to interpret complex human instructions, perceive and understand the visual context of ingredients, and execute precise bimanual actions to prepare the requested salad. We assessed the system's performance in terms of accuracy, efficiency, and adaptability to different salad recipes and human preferences through a series of experiments. Our results show a 100 % success rate in generating the correct executable code by the Language Module, a 96.06 % success rate in detecting specific ingredients by the Vision Module, and an overall success rate of 83.4 % in correctly executing user-requested tasks.

Skolkovo Institute of Science and Technology (RU)
Openalex Percentile: Top 4%
Robot Manipulation and Learning
5.25
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